Executive Clemency in Post-Furman Capital Cases

In the 1972 case of Furman v. Georgia, the United States Supreme Court invalidated virtually all existing death penalty statutes in the United States. Consequently, those jurisdictions that wanted to continue to execute were forced to revise their capital sentencing procedures. Since Furman,nearly all aspects of American death penalty law have been rewritten. Left unchanged by both the courts and the legislatures, however, are the ways in which states decide which death-sentenced inmates will have their sentences commuted through the powers of executive clemency

Validation and development of a cognitive behavioral task for a mouse model of Angelman syndrome

Angelman syndrome (AS) is a neurodevelopmental disorder that results from a loss of the paternally imprinted copy of the Ube3a gene. AS has a myriad of symptoms, including intellectual disabilities, lack of language comprehension or production, and an inability to coordinate movements. Hallmark disparities in higher order cognitive processes displayed by patients with AS are theorized to be encoded by the prefrontal cortex. To probe disease driven abnormalities in rodents, we used a task called the 5-choice serial reaction time task (5-CSRTT). The 5-CSRTT tests several higher order cognitive functions including attention, impulsivity, compulsivity, motivation, and other phenotypes important in the study of genetic and neuropsychiatric disorders. Previous work in the lab, however, has uncovered a possible flaw in the task as animals in both wild type and AS groups had problems properly learning the task. This was shown by both groups having an abnormally high number of started, but uncompleted trials (called omissions). The high number of omissions can represent a flaw in the experiment, characteristics of underlying pathology, or interactive effects of the two. Thus, we sought to optimize the parameters of the training to reduce the number of omissions. To investigate the effect that eating time has on the high number of omissions, the time it took a cohort of AS mice and a cohort of wild type mice to eat reward pellets during standardized training sessions was recorded. It was found that it takes significantly longer for AS mice to consume their reward pellet than wild type mice, but the eating time is not a significant contributor to the inflated omissions. By analyzing 5-CSRTT data from both AS and wild type mice, it was additionally discovered that AS mice have significantly higher proportion of omitted trials than wild type mice, but that there was no difference in accuracy between the two groups. Therefore, it is unlikely that the difference in the rate of omissions between the groups is due to underlying attentional deficits of the AS model mice. Furthermore, because it was also found that AS mice have significantly longer reward latencies and take longer to eat their reward pellets, there is evidence that the AS mice have deficits in motivational processes and in motor skills, which likely contributes to the omissions. Understanding the underlying process that affects these omissions is imperative for both validation of the behavioral task and to understand neurobiological differences in AS mice.Bachelor of Scienc

Labor market structure and fertility differences among Puerto Rican women: The effects of economic and social policies on opportunity costs

The oft-observed inverse relationship between economic activity in the formal or informal sector and levels of fertility is attributed to the opportunity costs of reproduction. The economic and social policies that initiate and maintain the substantial flow of federal transfer payments to the Puerto Rican population is likely to reduce the opportunity costs among women participating in the informal economy; therefore, informal labor market participants will have fertility levels more like women who have never worked than like women active in the formal labor market. Using data from the 1982 Puerto Rican Fertility and Family Planning Assessment, this paper compares fertility differentials among ever-married women who have never worked, who have ever worked in the informal economy, and who have only worked in the formal economy. Contrary to expectations, the fertility levels of informal labor market participants are more like those of formal labor market participants; economic activity in either sector is associated with bearing fewer children. Federal transfer payments do not appear to reduce the opportunity costs of reproduction among women employed in the informal economy. An earlier version of this paper was presented at the 1989 meeting of the Population Association of America.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43524/1/11113_2006_Article_BF02343246.pd

Non-Euclidean, convolutional learning on cortical brain surfaces

In recent years there have been many studies indicating that multiple cortical features, extracted at each surface vertex, are promising in the detection of various neurodevelopmental and neurodegenerative diseases. However, with limited datasets, it is challenging to train stable classifiers with such high-dimensional surface data. This necessitates a feature reduction that is commonly accomplished via regional volumetric morphometry from standard brain atlases. However, current regional summaries are not specific to the given age or pathology that is studied, which runs the risk of losing relevant information that can be critical in the classification process. To solve this issue, this paper proposes a novel data-driven approach by extending convolutional neural networks (CNN) for use on non-Euclidean manifolds such as cortical surfaces. The proposed network learns the most powerful features and brain regions from the extracted large dimensional feature space; thus creating a new feature space in which the dimensionality is reduced and feature distributions are better separated. We demonstrate the usability of the proposed surface-CNN framework in an example study classifying Alzheimers disease patients versus normal controls. The high performance in the cross-validation diagnostic results shows the potential of our proposed prediction system

Childhood Adversity Moderates Change in Latent Patterns of Psychological Adjustment during the COVID-19 Pandemic: Results of a Survey of U.S. Adults

Emerging evidence suggests that the consequences of childhood adversity impact later psychopathology by increasing individuals’ risk of experiencing difficulties in adjusting to stressful situations later in life. The goals of this study were to: (a) identify sociodemographic factors associated with subgroups of psychological adjustment prior to and after the onset of the COVID-19 pandemic and (b) examine whether and to what extent types of childhood adversity predict transition probabilities. Participants were recruited via multiple social media platforms and listservs. Data were collected via an internet-based survey. Our analyses reflect 1942 adults (M = 39.68 years); 39.8% reported experiencing at least one form of childhood adversity. Latent profile analyses (LPAs) and latent transition analyses (LTAs) were conducted to determine patterns of psychological adjustment and the effects of childhood adversity on transition probabilities over time. We identified five subgroups of psychological adjustment characterized by symptom severity level. Participants who were younger in age and those who endorsed marginalized identities exhibited poorer psychological adjustment during the pandemic. Childhood exposure to family and community violence and having basic needs met as a child (e.g., food, shelter) significantly moderated the relation between latent profile membership over time. Clinical and research implications are discussed

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson’s disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

The genetic architecture of the human cerebral cortex

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder